Detection and community-level identification of microbial mats in the McMurdo Dry Valleys using drone-based hyperspectral reflectance imaging

Abstract

The reflectance spectroscopic characteristics of cyanobacteria-dominated microbial mats in the McMurdo Dry Valleys (MDVs) were measured using a hyperspectral point spectrometer aboard an unmanned aerial system (remotely piloted aircraft system, unmanned aerial vehicle or drone) to determine whether mat presence, type and activity could be mapped at a spatial scale sufficient to characterize inter-annual change. Mats near Howard Glacier and Canada Glacier (ASPA 131) were mapped and mat samples were collected for DNA-based microbiome analysis. Although a broadband spectral parameter (a partial normalized difference vegetation index) identified mats, it missed mats in comparatively deep (> 10 cm) water or on bouldery surfaces where mats occupied fringing moats. A hyperspectral parameter (B6) did not have these shortcomings and recorded a larger dynamic range at both sites. When linked with colour orthomosaic data, B6 band strength is shown to be capable of characterizing the presence, type and activity of cyanobacteria-dominated mats in and around MDV streams. 16S rRNA gene polymerase chain reaction amplicon sequencing analysis of the mat samples revealed that dominant cyanobacterial taxa differed between spectrally distinguishable mats, indicating that spectral differences reflect underlying biological distinctiveness. Combined rapid-repeat hyperspectral measurements can be applied in order to monitor the distribution and activity of sentinel microbial ecosystems across the terrestrial Antarctic.

Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

“…Moreover, other types of vegetation cover, such as, e.g. microbiological mats, are distinguished by UAV as well (Levy et al 2020). Even during the summer period, these organisms are exposed to low temperature, strong wind, high irradiance and other stressors.…”

The Longest Baseline Record of Vegetation Dynamics in Antarctica Reveals Acute Sensitivity to Water Availability

“…This was most likely caused by the low spectral reflectance described for lichens in dry habitats in particular (Barták et al., 2018). However, accuracy might be improved in the future with the use of matched filtering techniques for the detection of lichens (Casanovas et al., 2015), ultra‐high resolution multi‐sensor observations (Lucieer et al., 2012), or hyperspectral image analysis (Jawak et al., 2019; Levy et al., 2020).…”

Remote Soil Moisture Measurement from Drone-Borne Reflectance Spectroscopy: Applications to Hydroperiod Measurement in Desert Playas

“…In addition, future drone-borne reflectance surveys could be designed to provide a spatial and temporal resolution bridge between multi-dataset orbital measurements, e.g., [16][17][18][19] and ground-based observations. For example, future drone-borne surveys could expand the aircraft sensor suite from SWIR (used in this study) to include visible/nearinfrared, e.g., [45] reflectance imagers alongside thermal infrared sensors [46], which could provide simultaneous NDVI and ground temperature measurements similar to those collected from orbit, e.g., [18,19].…”